Introduction:
Reka has developed a cutting-edge language model called Reka Flash to meet the demand for advanced language and vision models. This model performs exceptionally well on various language benchmarks, even with a smaller version called Reka Edge, which has only 7B trainable parameters. These models excel in diverse tasks and languages while using limited computational resources.
Features:
Reka Flash and Reka Edge are compared to existing models like Gemini Pro, GPT-3.5, and Llama-2 70B. They offer turbo-class and compact variant models, pretraining on text from 32 languages, and evaluation on various benchmarks including language understanding, reasoning, and multimodal interactions. Reka Flash competes with leading models on language benchmarks and vision tasks, while Reka Edge is designed for local deployments.
Functionality:
Reka Flash utilizes instruction tuning and reinforcement learning with PPO to enhance its chat capabilities, competing with models like GPT-4 and Gemini Pro. On the other hand, Reka Edge, optimized for local deployment, outperforms models like Llama 2 7B and Mistral 7B on standard language benchmarks, showcasing efficiency in resource-constrained environments.
In conclusion, Reka Flash and Reka Edge by Reka perform exceptionally well on language benchmarks using smaller resources, challenging models like Gemini Pro and GPT-4. Reka Flash excels in chat interactions with techniques like instruction tuning and reinforcement learning, while Reka Edge stands out for its efficiency in local deployments.